Package org.hipparchus.stat.descriptive

Generic univariate and multivariate summary statistic objects.

See: Description

Interface Summary

Interface	Description
AggregatableStatistic<T>	An interface for statistics that can aggregate results.
StatisticalMultivariateSummary	Reporting interface for basic multivariate statistics.
StatisticalSummary	Reporting interface for basic univariate statistics.
StorelessMultivariateStatistic	Base interface implemented by storeless multivariate statistics.
StorelessUnivariateStatistic	Extends the definition of UnivariateStatistic with StorelessUnivariateStatistic.increment(double) and StorelessUnivariateStatistic.incrementAll(double[]) methods for adding values and updating internal state.
UnivariateStatistic	Base interface implemented by all statistics.
WeightedEvaluation	Weighted evaluation for statistics.

Class Summary

Class	Description
AbstractStorelessUnivariateStatistic	Abstract base class for implementations of the StorelessUnivariateStatistic interface.
AbstractUnivariateStatistic	Abstract base class for implementations of the UnivariateStatistic interface.
DescriptiveStatistics	Maintains a dataset of values of a single variable and computes descriptive statistics based on stored data.
MultivariateSummaryStatistics	Computes summary statistics for a stream of n-tuples added using the addValue method.
StatisticalSummaryValues	Value object representing the results of a univariate statistical summary.
StreamingStatistics	Computes summary statistics for a stream of data values added using the addValue method.

Package org.hipparchus.stat.descriptive Description

Generic univariate and multivariate summary statistic objects.

UnivariateStatistic API Usage Examples:

UnivariateStatistic:

/∗ evaluation approach ∗/
double[] values = new double[] { 1, 2, 3, 4, 5 };
UnivariateStatistic stat = new Mean();
out.println("mean = " + stat.evaluate(values));


StorelessUnivariateStatistic:

/∗ incremental approach ∗/
double[] values = new double[] { 1, 2, 3, 4, 5 };
StorelessUnivariateStatistic stat = new Mean();
out.println("mean before adding a value is NaN = " + stat.getResult());
for (int i = 0; i < values.length; i++) {
stat.increment(values[i]);
out.println("current mean = " + stat2.getResult());
}
stat.clear();
out.println("mean after clear is NaN = " + stat.getResult());